Deep Learning-Based Noise Reduction Improves Optical Coherence Tomography Angiography Imaging of Radial Peripapillary Capillaries in Advanced Glaucoma.

Journal: Current eye research
Published Date: Dec 1, 2022

Abstract

PURPOSE: We applied deep learning-based noise reduction (NR) to optical coherence tomography-angiography (OCTA) images of the radial peripapillary capillaries (RPCs) in eyes with glaucoma and investigated the usefulness of this method as an objective analysis of glaucoma.

Authors

  • Kazuko Omodaka
    Department of Ophthalmology, Tohoku University Graduate School of Medicine, Miyagi, Japan.
  • Juun Horie
    Canon Inc, Tokyo, Japan.
  • Hikari Tokairin
    Department of Ophthalmology, Tohoku University Graduate School of Medicine, Sendai, Japan.
  • Chiho Kato
    Department of Ophthalmology, Tohoku University Graduate School of Medicine, Sendai, Japan.
  • Junko Ouchi
    Department of Ophthalmology, Tohoku University Graduate School of Medicine, Sendai, Japan.
  • Takahiro Ninomiya
    Department of Ophthalmology, Tohoku University Graduate School of Medicine, Miyagi, Japan.
  • Sharma Parmanand
    Department of Ophthalmology, Tohoku University Graduate School of Medicine, Sendai, Japan.
  • Satoru Tsuda
    Department of Ophthalmology, Graduate School of Medicine, Tohoku University Graduate School of Medicine, Sendai, Japan.
  • Toru Nakazawa
    Department of Ophthalmology, Tohoku University Graduate School of Medicine, Miyagi, Japan.

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